# Solvation directed drug design: from molecular physics to lead optimization

> **NIH NIH R35** · HERBERT H. LEHMAN COLLEGE · 2022 · $379,561

## Abstract

Project Summary
This project aims to develop new methods and computational tools that will speed structure-based drug-
discovery and apply these methods to identify new lead drug candidates for the mu-opioid receptor and SARS-
CoV-2 main proteases. This will be accomplished by providing a detailed analysis of hydration structure and
thermodynamics in targeted protein binding pockets then incorporating this information into docking and
water-based pharmacophore virtual screens. Key aims are to develop analysis tools that characterize and map
out solvation on the surfaces of drug target then utilize these solvation structural and thermodynamic maps to
improve computational methods of binding pocket druggability, virtual screening of purchasable compound
databases, and rational lead modification. Preliminary results for a new method of virtual screening that
combines constructing pharmacophores based on water-protein interactions with ROCS fast shape and pattern
matching show the method is greater than 3 orders of magnitude faster than computational docking.

## Key facts

- **NIH application ID:** 10330792
- **Project number:** 1R35GM144089-01
- **Recipient organization:** HERBERT H. LEHMAN COLLEGE
- **Principal Investigator:** Thomas Philip Kurtzman
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $379,561
- **Award type:** 1
- **Project period:** 2022-07-15 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10330792

## Citation

> US National Institutes of Health, RePORTER application 10330792, Solvation directed drug design: from molecular physics to lead optimization (1R35GM144089-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10330792. Licensed CC0.

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